# Copyright (c) 2022 Intel Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import logging

from ... import globals


class Calib_Dataloader(object):
    def __init__(self):
        pass

    def register_transformation(self):
        if globals.code_domain == "transformers_trainer":
            globals.list_calib_dataloader_name.append("trainer.get_eval_dataloader()")
        elif globals.code_domain == "transformers_no_trainer":
            pass
        elif globals.code_domain == "torchvision":
            globals.list_calib_dataloader_name.append("val_loader")
        elif globals.code_domain == "onnx":
            codes = open(globals.list_code_path[0], "r").read().split("\n")
            for line in codes:
                line = line.strip()
                if "loader" in line and "=" in line:
                    end = 0
                    for i in range(len(line)):
                        if line[i] == "=":
                            end = i
                    if line[end - 1] == " ":
                        globals.list_calib_dataloader_name.append(line[: end - 1])
                    else:
                        globals.list_calib_dataloader_name.append(line[:end])
        else:  # random model
            pass
